Flink1.12.1通过Table API / Flink SQL读取HBase2.4.0

昨天群里有人问 Flink 1.12 读取Hbase的问题，于是看到这篇文章分享给大家。本文作者Ashiamd。

1. 环境

废话不多说，这里用到的环境如下（不确定是否都必要，但是至少我是这个环境）

zookeeper 3.6.2
Hbase 2.4.0
Flink 1.12.1

2. HBase表

# 创建表
create 'u_m_01' , 'u_m_r'

# 插入数据
put 'u_m_01', 'a,A', 'u_m_r:r' , '1'
put 'u_m_01', 'a,B', 'u_m_r:r' , '3'
put 'u_m_01', 'b,B', 'u_m_r:r' , '3'
put 'u_m_01', 'b,C', 'u_m_r:r' , '4'
put 'u_m_01', 'c,A', 'u_m_r:r' , '2'
put 'u_m_01', 'c,C', 'u_m_r:r' , '5'
put 'u_m_01', 'c,D', 'u_m_r:r' , '1'
put 'u_m_01', 'd,B', 'u_m_r:r' , '5'
put 'u_m_01', 'd,D', 'u_m_r:r' , '2'
put 'u_m_01', 'e,A', 'u_m_r:r' , '3'
put 'u_m_01', 'e,B', 'u_m_r:r' , '2'
put 'u_m_01', 'f,A', 'u_m_r:r' , '1'
put 'u_m_01', 'f,B', 'u_m_r:r' , '2'
put 'u_m_01', 'f,D', 'u_m_r:r' , '3'
put 'u_m_01', 'g,C', 'u_m_r:r' , '1'
put 'u_m_01', 'g,D', 'u_m_r:r' , '4'
put 'u_m_01', 'h,A', 'u_m_r:r' , '1'
put 'u_m_01', 'h,B', 'u_m_r:r' , '2'
put 'u_m_01', 'h,C', 'u_m_r:r' , '4'
put 'u_m_01', 'h,D', 'u_m_r:r' , '5'

3. pom依赖

jdk1.8
Flink1.12.1 使用的pom依赖如下（有些是多余的）

<?xml version="1.0" encoding="UTF-8"?>
="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    >4.0.0</modelVersion>

    >org.example</groupId>
    >flink-hive-hbase</artifactId>
    >1.0-SNAPSHOT</version>

    >
        .compiler.source>8</maven.compiler.source>
        .compiler.target>8</maven.compiler.target>
        .version>1.12.1</flink.version>
        .binary.version>2.12</scala.binary.version>
        .version>3.1.2</hive.version>
        .version>8.0.19</mysql.version>
        .version>2.4.0</hbase.version>
    </properties>


    >

        <!-- Flink -->
        >
            >org.apache.flink</groupId>
            >flink-java</artifactId>
            >${flink.version}</version>
        </dependency>
        >
            >org.apache.flink</groupId>
            >flink-streaming-java_${scala.binary.version}</artifactId>
            >${flink.version}</version>
        </dependency>
        >
            >org.apache.flink</groupId>
            >flink-clients_${scala.binary.version}</artifactId>
            >${flink.version}</version>
        </dependency>

        <!-- HBase -->
        >
            >org.apache.flink</groupId>
            >flink-connector-hbase-2.2_${scala.binary.version}</artifactId>
            >${flink.version}</version>
        </dependency>
        >
            >org.apache.hbase</groupId>
            >hbase-server</artifactId>
            >${hbase.version}</version>
        </dependency>
        >
            >org.apache.hbase</groupId>
            >hbase-client</artifactId>
            >${hbase.version}</version>
        </dependency>


        <!--        <;!&ndash; JDBC &ndash;>;-->
<!--        >-->
<!--            >org.apache.flink</groupId>-->
<!--            >flink-connector-jdbc_${scala.binary.version}</artifactId>-->
<!--            >${flink.version}</version>-->
<!--        </dependency>-->

<!--        <;!&ndash; mysql &ndash;>;-->
<!--        >-->
<!--            >mysql</groupId>-->
<!--            >mysql-connector-java</artifactId>-->
<!--            >${mysql.version}</version>-->
<!--        </dependency>-->

<!--        <;!&ndash; Hive Dependency &ndash;>;-->
<!--        >-->
<!--            >org.apache.hive</groupId>-->
<!--            >hive-exec</artifactId>-->
<!--            >${hive.version}</version>-->
<!--        </dependency>-->
<!--        >-->
<!--            >org.apache.flink</groupId>-->
<!--            >flink-connector-hive_${scala.binary.version}</artifactId>-->
<!--            >${flink.version}</version>-->
<!--        </dependency>-->

        <!-- Table API -->
        >
            >org.apache.flink</groupId>
            >flink-table-planner-blink_${scala.binary.version}</artifactId>
            >${flink.version}</version>
        </dependency>
        >
            >org.apache.flink</groupId>
            >flink-table-planner_${scala.binary.version}</artifactId>
            >${flink.version}</version>
        </dependency>

        <!-- csv -->
        >
            >org.apache.flink</groupId>
            >flink-csv</artifactId>
            >${flink.version}</version>
        </dependency>

<!--        <;!&ndash; Lombok &ndash;>;-->
<!--        >-->
<!--            >org.projectlombok</groupId>-->
<!--            >lombok</artifactId>-->
<!--            >1.18.18</version>-->
<!--        </dependency>-->

    </dependencies>
</project>

4. Flink-Java代码

用到的pojo类

package entity;
import java.io.Serializable;

public class UserMovie implements Serializable {
    @Override
    public String toString() {
        return "UserMovie{" +
                "userId='" + userId + '\'' +
                ", movieId='" + movieId + '\'' +
                ", ratting=" + ratting +
                '}';
    }

    public static long getSerialVersionUID() {
        return serialVersionUID;
    }

    public String getUserId() {
        return userId;
    }

    public void setUserId(String userId) {
        this.userId = userId;
    }

    public String getMovieId() {
        return movieId;
    }

    public void setMovieId(String movieId) {
        this.movieId = movieId;
    }

    public Double getRatting() {
        return ratting;
    }

    public void setRatting(Double ratting) {
        this.ratting = ratting;
    }

    public UserMovie() {
    }

    public UserMovie(String userId, String movieId, Double ratting) {
        this.userId = userId;
        this.movieId = movieId;
        this.ratting = ratting;
    }

    private static final long serialVersionUID = 256158274329337559L;

    private String userId;

    private String movieId;

    private Double ratting;

}

实际测试代码

package hbase;

import com.nimbusds.jose.util.IntegerUtils;
import entity.UserMovie;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.TableResult;
import org.apache.flink.types.Row;
import org.apache.flink.util.CloseableIterator;
import org.apache.flink.util.StringUtils;

import java.util.ArrayList;
import java.util.List;
import java.util.function.Consumer;

public class HBaseTest_01   {
    public static void main(String[] args) throws Exception {
        // 批执行环境
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

        // 表环境
        EnvironmentSettings settings = EnvironmentSettings.newInstance()
                .useBlinkPlanner()
                .inBatchMode()
                .build();
        TableEnvironment tableEnv = TableEnvironment.create(settings);

        // 创建用户-电影表 u_m
        TableResult tableResult = tableEnv.executeSql(
                "CREATE TABLE u_m (" +
                        " rowkey STRING," +
                        " u_m_r ROW," +
                        " PRIMARY KEY (rowkey) NOT ENFORCED" +
                        " ) WITH (" +
                        " 'connector' = 'hbase-2.2' ," +
                        " 'table-name' = 'default:u_m_01' ," +
                        " 'zookeeper.quorum' = '127.0.0.1:2181'" +
                        " )");

        // 查询是否能获取到HBase里的数据
//        Table table = tableEnv.sqlQuery("SELECT rowkey, u_m_r FROM u_m");

        // 相当于 scan
        Table table = tableEnv.sqlQuery("SELECT * FROM u_m");

        // 查询的结果
        TableResult executeResult = table.execute();

        // 获取查询结果
        CloseableIterator> collect = executeResult.collect();

        // 输出 (执行print或者下面的 Consumer之后，数据就被消费了。两个只能留下一个)
        executeResult.print();

        List> userMovieList = new ArrayList<>();

        collect.forEachRemaining(new Consumer>() {
            @Override
            public void accept(Row row) {
                String field0 = String.valueOf(row.getField(0));
                String[] user_movie = field0.split(",");
                Double ratting = Double.valueOf(String.valueOf(row.getField(1)));
                userMovieList.add(new UserMovie(user_movie[0],user_movie[1],ratting));
            }
        });


        System.out.println("................");

        for(UserMovie um : userMovieList){
            System.out.println(um);
        }
    }
}

5. 输出

没有注解掉第59行代码executeResult.print();时

+--------------------------------+--------------------------------+
|                         rowkey |                          u_m_r |
+--------------------------------+--------------------------------+
|                            a,A |                              1 |
|                            a,B |                              3 |
|                            b,B |                              3 |
|                            b,C |                              4 |
|                            c,A |                              2 |
|                            c,C |                              5 |
|                            c,D |                              1 |
|                            d,B |                              5 |
|                            d,D |                              2 |
|                            e,A |                              3 |
|                            e,B |                              2 |
|                            f,A |                              1 |
|                            f,B |                              2 |
|                            f,D |                              3 |
|                            g,C |                              1 |
|                            g,D |                              4 |
|                            h,A |                              1 |
|                            h,B |                              2 |
|                            h,C |                              4 |
|                            h,D |                              5 |
+--------------------------------+--------------------------------+
20 rows in set
................

注解掉第59行代码executeResult.print();时

................
UserMovie{userId='a', movieId='A', ratting=1.0}
UserMovie{userId='a', movieId='B', ratting=3.0}
UserMovie{userId='b', movieId='B', ratting=3.0}
UserMovie{userId='b', movieId='C', ratting=4.0}
UserMovie{userId='c', movieId='A', ratting=2.0}
UserMovie{userId='c', movieId='C', ratting=5.0}
UserMovie{userId='c', movieId='D', ratting=1.0}
UserMovie{userId='d', movieId='B', ratting=5.0}
UserMovie{userId='d', movieId='D', ratting=2.0}
UserMovie{userId='e', movieId='A', ratting=3.0}
UserMovie{userId='e', movieId='B', ratting=2.0}
UserMovie{userId='f', movieId='A', ratting=1.0}
UserMovie{userId='f', movieId='B', ratting=2.0}
UserMovie{userId='f', movieId='D', ratting=3.0}
UserMovie{userId='g', movieId='C', ratting=1.0}
UserMovie{userId='g', movieId='D', ratting=4.0}
UserMovie{userId='h', movieId='A', ratting=1.0}
UserMovie{userId='h', movieId='B', ratting=2.0}
UserMovie{userId='h', movieId='C', ratting=4.0}
UserMovie{userId='h', movieId='D', ratting=5.0}

注意

这里我们在Flink在SQL里面定义HBase的Table时，指定的字段都是用的STRING类型，虽然本来应该是INT，但是用INT的时候，报错了，改成INT就ok了。

大数据架构师

Flink1.12.1通过Table API / Flink SQL读取HBase2.4.0

1. 环境

2. HBase表

3. pom依赖

4. Flink-Java代码

5. 输出

注意

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